We focus on improving the effectiveness of a Virtual Assistant (VA) in recognizing emerging entities in spoken queries. We introduce a method that uses historical user interactions to forecast which entities will gain in popularity and become trending, and it subsequently integrates the predictions within the Automated Speech Recognition (ASR) component of the VA. Experiments show that our proposed approach results in a 20% relative reduction in errors on emerging entity name utterances without degrading the overall recognition quality of the system.
@article{arxiv.2005.12816,
title = {Predicting Entity Popularity to Improve Spoken Entity Recognition by Virtual Assistants},
author = {Christophe Van Gysel and Manos Tsagkias and Ernest Pusateri and Ilya Oparin},
journal= {arXiv preprint arXiv:2005.12816},
year = {2020}
}
Comments
SIGIR '20. The 43rd International ACM SIGIR Conference on Research & Development in Information Retrieval